Search Results for author: Vishal Monga

Found 48 papers, 11 papers with code

Deep, convergent, unrolled half-quadratic splitting for image deconvolution

1 code implementation20 Feb 2024 Yanan Zhao, Yuelong Li, Haichuan Zhang, Vishal Monga, Yonina C. Eldar

Through extensive experimental studies, we verify that our approach achieves competitive performance with state-of-the-art unrolled layer-specific learning and significantly improves over the traditional HQS algorithm.

Deblurring Image Deblurring +1

Maturity-Aware Active Learning for Semantic Segmentation with Hierarchically-Adaptive Sample Assessment

1 code implementation28 Aug 2023 Amirsaeed Yazdani, Xuelu Li, Vishal Monga

We propose "Maturity-Aware Distribution Breakdown-based Active Learning'' (MADBAL), an AL method that benefits from a hierarchical approach to define a multiview data distribution, which takes into account the different "sample" definitions jointly, hence able to select the most impactful segmentation pixels with comprehensive understanding.

Active Learning Segmentation +1

Iterative, Deep Synthetic Aperture Sonar Image Segmentation

no code implementations28 Mar 2022 Yung-Chen Sun, Isaac D. Gerg, Vishal Monga

IDUS is an unsupervised learning framework that can be divided into four main steps: 1) A deep network estimates class assignments.

Image Segmentation Segmentation +2

GlideNet: Global, Local and Intrinsic based Dense Embedding NETwork for Multi-category Attributes Prediction

1 code implementation CVPR 2022 Kareem Metwaly, Aerin Kim, Elliot Branson, Vishal Monga

Collectively, the Global-Local-Intrinsic blocks comprehend the scene's global context while attending to the characteristics of the local object of interest.

Attribute Multi-Label Classification

Deep Algorithm Unrolling for Biomedical Imaging

no code implementations15 Aug 2021 Yuelong Li, Or Bar-Shira, Vishal Monga, Yonina C. Eldar

In this chapter, we review biomedical applications and breakthroughs via leveraging algorithm unrolling, an important technique that bridges between traditional iterative algorithms and modern deep learning techniques.

Image Generation Rolling Shutter Correction

Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation

no code implementations30 Jul 2021 Yung-Chen Sun, Isaac D. Gerg, Vishal Monga

Our results show that the performance of our proposed method is considerably better than current state-of-the-art methods in SAS image segmentation.

Image Segmentation Segmentation +2

Physically Inspired Dense Fusion Networks for Relighting

1 code implementation5 May 2021 Amirsaeed Yazdani, Tiantong Guo, Vishal Monga

While our proposed method applies to both one-to-one and any-to-any relighting problems, for each case we introduce problem-specific components that enrich the model performance: 1) For one-to-one relighting we incorporate normal vectors of the surfaces in the scene to adjust gloss and shadows accordingly in the image.

Image Relighting Intrinsic Image Decomposition

Simultaneous Denoising and Localization Network for Photoacoustic Target Localization

no code implementations30 Apr 2021 Amirsaeed Yazdani, Sumit Agrawal, Kerrick Johnstonbaugh, Sri-Rajasekhar Kothapalli, Vishal Monga

The network trained on this novel dataset accurately locates targets in experimental PA data that is clinically relevant with respect to the localization of vessels, needles, or brachytherapy seeds.


Multi-Class Micro-CT Image Segmentation Using Sparse Regularized Deep Networks

no code implementations21 Apr 2021 Amirsaeed Yazdani, Yung-Chen Sun, Nicholas B. Stephens, Timothy Ryan, Vishal Monga

It is common in anthropology and paleontology to address questions about extant and extinct species through the quantification of osteological features observable in micro-computed tomographic (micro-CT) scans.

Image Segmentation Segmentation +1

Real-Time, Deep Synthetic Aperture Sonar (SAS) Autofocus

no code implementations18 Mar 2021 Isaac D. Gerg, Vishal Monga

To improve convergence, a hand-crafted weighting function to remove "bad" areas of the image is sometimes applied to the image-under-test before the optimization procedure.

Image Reconstruction

Deep Autofocus for Synthetic Aperture Sonar

no code implementations29 Oct 2020 Isaac Gerg, Vishal Monga

In this letter, we demonstrate the potential of machine learning, specifically deep learning, to address the autofocus problem.

Deblurring Image Reconstruction

Structural Prior Driven Regularized Deep Learning for Sonar Image Classification

no code implementations26 Oct 2020 Isaac D. Gerg, Vishal Monga

Deep learning has been recently shown to improve performance in the domain of synthetic aperture sonar (SAS) image classification.

General Classification Image Classification

Group Based Deep Shared Feature Learning for Fine-grained Image Classification

no code implementations4 Apr 2020 Xuelu Li, Vishal Monga

Given that images from distinct classes in fine-grained classification share significant features of interest, we present a new deep network architecture that explicitly models shared features and removes their effect to achieve enhanced classification results.

Classification Fine-Grained Image Classification +1

Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors

no code implementations10 Sep 2019 Venkateswararao Cherukuri, Tiantong Guo, Steve. J. Schiff, Vishal Monga

Sharpness is emphasized by the variance of the Laplacian which we show can be implemented by a fixed feedback layer at the output of the network.

Image Enhancement Image Super-Resolution

Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks

no code implementations22 Apr 2019 Tiantong Guo, Hojjat S. Mousavi, Vishal Monga

As the first contribution, we show that DCT can be integrated into the network structure as a Convolutional DCT (CDCT) layer.

Image Super-Resolution

An Algorithm Unrolling Approach to Deep Image Deblurring

no code implementations9 Feb 2019 Yuelong Li, Mohammad Tofighi, Vishal Monga, Yonina C. Eldar

We first present an iterative algorithm that may be considered a generalization of the traditional total-variation regularization method on the gradient domain, and subsequently unroll the half-quadratic splitting algorithm to construct a neural network.

Blind Image Deblurring Image Deblurring +1

Deep Algorithm Unrolling for Blind Image Deblurring

no code implementations9 Feb 2019 Yuelong Li, Mohammad Tofighi, Junyi Geng, Vishal Monga, Yonina C. Eldar

We then unroll the algorithm to construct a neural network for image deblurring which we refer to as Deep Unrolling for Blind Deblurring (DUBLID).

Blind Image Deblurring Image Deblurring +1

Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection

no code implementations21 Jan 2019 Mohammad Tofighi, Tiantong Guo, Jairam K. P. Vanamala, Vishal Monga

Using a set of canonical cell nuclei shapes, prepared with the help of a domain expert, we develop a new approach that we call Shape Priors with Convolutional Neural Networks (SP-CNN).

Classifying Multi-channel UWB SAR Imagery via Tensor Sparsity Learning Techniques

1 code implementation4 Oct 2018 Tiep Vu, Lam Nguyen, Vishal Monga

Using low-frequency (UHF to L-band) ultra-wideband (UWB) synthetic aperture radar (SAR) technology for detecting buried and obscured targets, e. g. bomb or mine, has been successfully demonstrated recently.

Dictionary Learning General Classification +1

Deep Image Super Resolution via Natural Image Priors

no code implementations8 Feb 2018 Hojjat S. Mousavi, Tiantong Guo, Vishal Monga

Single image super-resolution (SR) via deep learning has recently gained significant attention in the literature.

Image Super-Resolution

Orthogonally Regularized Deep Networks For Image Super-resolution

no code implementations6 Feb 2018 Tiantong Guo, Hojjat S. Mousavi, Vishal Monga

Deep learning methods, in particular trained Convolutional Neural Networks (CNNs) have recently been shown to produce compelling state-of-the-art results for single image Super-Resolution (SR).

Image Super-Resolution

Deep Network for Simultaneous Decomposition and Classification in UWB-SAR Imagery

no code implementations16 Jan 2018 Tiep Vu, Lam Nguyen, Tiantong Guo, Vishal Monga

The classification problem has been firstly, and partially, addressed by sparse representation-based classification (SRC) method which can extract noise from signals and exploit the cross-channel information.

Classification Denoising +2

Bridging the Gap: Simultaneous Fine Tuning for Data Re-Balancing

no code implementations8 Jan 2018 John McKay, Isaac Gerg, Vishal Monga

There are many real-world classification problems wherein the issue of data imbalance (the case when a data set contains substantially more samples for one/many classes than the rest) is unavoidable.

General Classification

Blind Image Deblurring Using Row-Column Sparse Representations

no code implementations5 Dec 2017 Mohammad Tofighi, Yuelong Li, Vishal Monga

Blind image deblurring is a particularly challenging inverse problem where the blur kernel is unknown and must be estimated en route to recover the deblurred image.

Blind Image Deblurring Image Deblurring

Fast Stochastic Hierarchical Bayesian MAP for Tomographic Imaging

no code implementations7 Jul 2017 John McKay, Raghu G. Raj, Vishal Monga

The resulting algorithm, fast stochastic HB-MAP (fsHBMAP), takes dramatically fewer operations while retaining high reconstruction quality.

What's Mine is Yours: Pretrained CNNs for Limited Training Sonar ATR

no code implementations29 Jun 2017 John McKay, Isaac Gerg, Vishal Monga, Raghu Raj

Finding mines in Sonar imagery is a significant problem with a great deal of relevance for seafaring military and commercial endeavors.

Transfer Learning

Robust Sonar ATR Through Bayesian Pose Corrected Sparse Classification

no code implementations26 Jun 2017 John McKay, Vishal Monga, Raghu G. Raj

Sonar imaging has seen vast improvements over the last few decades due in part to advances in synthetic aperture Sonar (SAS).

Anomaly Detection Classification +2

Using Frame Theoretic Convolutional Gridding for Robust Synthetic Aperture Sonar Imaging

no code implementations26 Jun 2017 John McKay, Anne Gelb, Vishal Monga, Raghu Raj

Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency.

A Maximum A Posteriori Estimation Framework for Robust High Dynamic Range Video Synthesis

no code implementations8 Dec 2016 Yuelong Li, Chul Lee, Vishal Monga

For HDR video, a stiff practical challenge presents itself in the form of accurate correspondence estimation of objects between video frames.

Image Generation Optical Flow Estimation

Fast Low-rank Shared Dictionary Learning for Image Classification

2 code implementations27 Oct 2016 Tiep Vu, Vishal Monga

Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries.

Classification Dictionary Learning +2

Adaptive matching pursuit for sparse signal recovery

no code implementations12 Sep 2016 Tiep H. Vu, Hojjat S. Mousavi, Vishal Monga

Spike and Slab priors have been of much recent interest in signal processing as a means of inducing sparsity in Bayesian inference.

Bayesian Inference

Learning a low-rank shared dictionary for object classification

2 code implementations31 Jan 2016 Tiep H. Vu, Vishal Monga

Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns.

Classification Dictionary Learning +2

Localized Dictionary design for Geometrically Robust Sonar ATR

no code implementations13 Jan 2016 John McKay, Vishal Monga, Raghu Raj

We develop a new localized block-based dictionary design that can enable geometric, i. e. pose robustness.

Dictionary Learning General Classification +1

Discriminative Sparsity for Sonar ATR

no code implementations1 Jan 2016 John McKay, Raghu Raj, Vishal Monga, Jason Isaacs

Advancements in Sonar image capture have enabled researchers to apply sophisticated object identification algorithms in order to locate targets of interest in images such as mines.

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

2 code implementations16 Jun 2015 Tiep Huu Vu, Hojjat Seyed Mousavi, Vishal Monga, Arvind UK Rao, Ganesh Rao

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures.

Classification Dictionary Learning +2

ICR: Iterative Convex Refinement for Sparse Signal Recovery Using Spike and Slab Priors

no code implementations16 Feb 2015 Hojjat S. Mousavi, Vishal Monga, Trac. D. Tran

Essentially, ICR solves a sequence of convex optimization problems such that sequence of solutions converges to a sub-optimal solution of the original hard optimization problem.

DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification

no code implementations3 Feb 2015 Tiep H. Vu, Hojjat S. Mousavi, Vishal Monga, UK Arvind Rao, Ganesh Rao

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structure.

Classification Dictionary Learning +3

Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors

no code implementations30 Jan 2015 Hojjat Seyed Mousavi, Umamahesh Srinivas, Vishal Monga, Yuanming Suo, Minh Dao, Trac. D. Tran

Promising results have been achieved in image classification problems by exploiting the discriminative power of sparse representations for classification (SRC).

Classification Face Recognition +2

Discriminative Local Sparse Representations for Robust Face Recognition

no code implementations8 Nov 2011 Yi Chen, Umamahesh Srinivas, Thong T. Do, Vishal Monga, Trac. D. Tran

We propose a probabilistic graphical model framework to explicitly mine the conditional dependencies between these distinct sparse local features.

Face Recognition General Classification +1

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